Dual Encryption Technology via Laser‐Induced Perovskite Multicolor and Textures Patterning With Artificial Intelligence Recognition

ABSTRACT Lead halide perovskite films show luminescence ideal for security, but artificial intelligence (AI) advancements have rendered their traditional display encryption obsolete. Herein, for AI recognition, we developed a facile and highly secure dual encryption method based on laser‐induced perovskite multicolor and textures patterning. Precise control of the emission wavelength and surface texture of the perovskite composite film (PCF) was achieved by regulating the composition of the anion exchange solution and laser path. A Quick Response (QR) code consisting of squares with different emission wavelengths and textures was fabricated on CsPbBr 3 PCF. The decryption process requires two keys. The first key is an optical filter, which is used to selectively isolate squares emitting at specific wavelength. Another key is the high resolution surface texture of the patterned squares. Further screening of squares with the specified texture is performed via pattern recognition using the YOLOv5 model, thereby achieving decryption of the QR code content. The YOLOv5 model achieved an average similarity of 89.5% in recognizing training samples, with a precision of 96.44%, which means the chosen model exhibited effective recognition performance. This strategy successfully realized dual encryption of information and provided a novel solution for information security protection with AI recognition.

Authors

Institutions

Publication Details

Journal
Laser & Photonics Review
Published
2026-05-21
DOI
https://doi.org/10.1002/lpor.71341
Primary Topic
Perovskite Materials and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dual Encryption Technology via Laser‐Induced Perovskite Multicolor and Textures Patterning With Artificial Intelligence Recognition

J Zhang, J C Chen, Fengyi Zhang, Rongqiu Lv et al.
Laser & Photonics Review
Perovskite Materials and Applications
article

Dual Encryption Technology via Laser‐Induced Perovskite Multicolor and Textures Patterning With Artificial Intelligence Recognition

J Zhang, J C Chen, Fengyi Zhang, Rongqiu Lv, Junyi You, Bin Wang, Shiyan Tong, Haibo Zeng
article en

Abstract

ABSTRACT Lead halide perovskite films show luminescence ideal for security, but artificial intelligence (AI) advancements have rendered their traditional display encryption obsolete. Herein, for AI recognition, we developed a facile and highly secure dual encryption method based on laser‐induced perovskite multicolor and textures patterning. Precise control of the emission wavelength and surface texture of the perovskite composite film (PCF) was achieved by regulating the composition of the anion exchange solution and laser path. A Quick Response (QR) code consisting of squares with different emission wavelengths and textures was fabricated on CsPbBr 3 PCF. The decryption process requires two keys. The first key is an optical filter, which is used to selectively isolate squares emitting at specific wavelength. Another key is the high resolution surface texture of the patterned squares. Further screening of squares with the specified texture is performed via pattern recognition using the YOLOv5 model, thereby achieving decryption of the QR code content. The YOLOv5 model achieved an average similarity of 89.5% in recognizing training samples, with a precision of 96.44%, which means the chosen model exhibited effective recognition performance. This strategy successfully realized dual encryption of information and provided a novel solution for information security protection with AI recognition.

Laser & Photonics Review
Southeast University (CN), Ministry of Industry and Information Technology (CN)
Openalex Percentile: Top 8%
Perovskite Materials and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.